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Finding Moving-Band Statistical Arbitrages via Convex-Concave Optimization

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  • Kasper Johansson
  • Thomas Schmelzer
  • Stephen Boyd

Abstract

We propose a new method for finding statistical arbitrages that can contain more assets than just the traditional pair. We formulate the problem as seeking a portfolio with the highest volatility, subject to its price remaining in a band and a leverage limit. This optimization problem is not convex, but can be approximately solved using the convex-concave procedure, a specific sequential convex programming method. We show how the method generalizes to finding moving-band statistical arbitrages, where the price band midpoint varies over time.

Suggested Citation

  • Kasper Johansson & Thomas Schmelzer & Stephen Boyd, 2024. "Finding Moving-Band Statistical Arbitrages via Convex-Concave Optimization," Papers 2402.08108, arXiv.org.
    • Handle: RePEc:arx:papers:2402.08108
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    References listed on IDEAS

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